{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T12:17:34Z","timestamp":1789129054362,"version":"build-2803163510"},"reference-count":40,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM138778"],"award-info":[{"award-number":["R01GM138778"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000052","name":"NIH Office of the Director","doi-asserted-by":"publisher","award":["R01GM138778\u201004S1"],"award-info":[{"award-number":["R01GM138778\u201004S1"]}],"id":[{"id":"10.13039\/100000052","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alzheimer's &amp; Dementia"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION<\/jats:title>\n                    <jats:p>Artificial intelligence (AI) models have been applied to differential dementia detection tasks in brain images from curated, high\u2010quality benchmark databases, but not real\u2010world data in hospitals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>We describe a deep learning model specially trained for disease detection in heterogeneous clinical images from electronic health records without focusing on confounding factors. It encodes up to 14 multimodal images, alongside age and demographics, and outputs the likelihood of vascular dementia, Alzheimer's, Lewy body dementia, Pick's disease, mild cognitive impairment, and unspecified dementia. We use data from Massachusetts General Hospital (183,018 images from 11,015 patients) for training and external data (125,493 images from 6,662 patients) for testing.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Performance ranged between 0.82 and 0.94 area under the curve (AUC) on data from 1003 sites.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>Analysis shows that the model focused on subcortical brain structures as the basis for its decisions. By detecting biomarkers in real\u2010world data, the presented techniques will help with clinical translation of disease detection AI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Our artificial intelligence (AI) model can detect neurodegenerative disorders in brain imaging electronic health record (EHR) data.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>It encodes up to 14 brain images and text information from a single patient's EHR.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Attention maps show that the model focuses on subcortical brain structures.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Performance ranged from 0.82 to 0.94 area under the curve (AUC) on data from 1003 external sites.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.70362","type":"journal-article","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T23:55:28Z","timestamp":1751414128000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Differential dementia detection from multimodal brain images in a real\u2010world dataset"],"prefix":"10.1002","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9631-2567","authenticated-orcid":false,"given":"Matthew","family":"Leming","sequence":"first","affiliation":[{"name":"Center for Systems Biology Massachusetts General Hospital  Boston USA"},{"name":"Massachusetts Alzheimer's Disease Research Center Massachusetts General Hospital  Boston USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0626-1346","authenticated-orcid":false,"given":"Hyungsoon","family":"Im","sequence":"additional","affiliation":[{"name":"Center for Systems Biology Massachusetts General Hospital  Boston USA"},{"name":"Massachusetts Alzheimer's Disease Research Center Massachusetts General Hospital  Boston USA"},{"name":"Department of Radiology Massachusetts General Hospital  Boston USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2017.08.017"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1101\/757054"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101694"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg\u20102020\u2010017099"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746\u2010023\u201000868\u2010x"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256\u2010024\u201000797\u20108"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12051068"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3224727"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746\u2010024\u201001235\u20100"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/s43588\u2010023\u201000573\u20105"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117287"},{"key":"e_1_2_8_13_1","article-title":"SynthSeg: domain randomisation for segmentation of brain scans of any contrast and resolution","author":"Billot B","year":"2021","journal-title":"arXiv"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00259\u2010020\u201004969\u20107"},{"key":"e_1_2_8_15_1","unstructured":"Dementias NIH: National Institute of Neurological Disorders and Stroke; 2024 [cited 2024 12\u20103\u20102024]. Available from:https:\/\/www.ninds.nih.gov\/health\u2010information\/disorders\/dementias"},{"key":"e_1_2_8_16_1","article-title":"An image is worth 16\u00d716 words: transformers for image recognition at scale","author":"Dosovitskiy A","journal-title":"arXiv. 2020"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467\u2010020\u201019784\u20109"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102076"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0277572"},{"key":"e_1_2_8_20_1","first-page":"2672","volume-title":"Advances in Neural Information Processing Systems","author":"Goodfellow IJ","year":"2014"},{"key":"e_1_2_8_21_1","article-title":"A simple unified framework for detecting out\u2010of\u2010distribution samples and adversarial attacks","author":"Lee K","year":"2018","journal-title":"arXiv"},{"key":"e_1_2_8_22_1","volume-title":"Auto\u2010Encoding Variational Bayes","author":"Kingma DP","year":"2013"},{"key":"e_1_2_8_23_1","article-title":"Why do tree\u2010based models still outperform deep learning on tabular data?","author":"Grinsztajn L","year":"2022","journal-title":"arXiv"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainresrev.2005.11.007"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.3389\/fcvm.2020.00005"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2018.00330"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.4103\/1008\u2010682X.179528"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1002\/alz.12308"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/alz.12690"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.1176\/ajp.157.1.16"},{"key":"e_1_2_8_31_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awn146"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304\u20103940(96)12775\u20100"},{"key":"e_1_2_8_33_1","doi-asserted-by":"publisher","DOI":"10.1097\/WAD.0b013e3182163b62"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci11091134"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2022.103311"},{"key":"e_1_2_8_36_1","doi-asserted-by":"publisher","DOI":"10.1093\/braincomms\/fcab211"},{"key":"e_1_2_8_37_1","doi-asserted-by":"publisher","DOI":"10.1111\/jgs.17183"},{"key":"e_1_2_8_38_1","doi-asserted-by":"publisher","DOI":"10.1377\/hlthaff.2022.00185"},{"key":"e_1_2_8_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2022.102309"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.3233\/JAD\u2010161261"},{"key":"e_1_2_8_41_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746\u2010020\u20100221\u2010y"}],"container-title":["Alzheimer's &amp; Dementia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/alz.70362","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/alz.70362","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/alz.70362","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T15:57:49Z","timestamp":1784303869000},"score":1,"resource":{"primary":{"URL":"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/10.1002\/alz.70362"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":40,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,7]]}},"alternative-id":["10.1002\/alz.70362"],"URL":"https:\/\/doi.org\/10.1002\/alz.70362","archive":["Portico"],"relation":{},"ISSN":["1552-5260","1552-5279"],"issn-type":[{"value":"1552-5260","type":"print"},{"value":"1552-5279","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7]]},"assertion":[{"value":"2025-01-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-15","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70362"}}